Search NASA⌕ Search

SEARCH · Search NASA

Results for “Code Robustness”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 541 records · Page 30
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

MAESTROeX: A Massively Parallel Low Mach Number Astrophysical Solver

@e present MAESTROeX, a massively parallel solver for low Mach number astrophysical flows. The underlying low Mach number equation set allows for efficient, long-time integration for highly subsonic flows compared to compressible approaches. MAESTROeX is suitable for modeling full spherical stars as well as well as planar simulations of dynamics within localized regions of a star, and can robustly handle several orders of magnitude of density and pressure stratification. Previously, we have described the development of the predecessor of MAESTROeX, called MAESTRO, in a series of papers. Here, we present a new, greatly simplified temporal integration scheme that retains the same order of accuracy as our previous approaches. We also explore the use of alternative spatial mapping of the one-dimensional base state onto the full Cartesian grid. The code leverages the new AMReX software framework for block-structured adaptive mesh refinement (AMR) applications, allowing for scalability to large fractions of leadership-class machines. Finally, using our previous studies on the convective phase of single-degenerate progenitor models of SNe Ia as a guide, we characterize the performance of the code and validate the new algorithmic features. Like MAESTRO, MAESTROeX is fully open source.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Characterization of a Polyethylene Moderated Highly Enriched Uranium System

The polyethylene interstitial materials for the Class Foils experiment are one of the teaching tools used to teach criticality safety at the National Criticality Experiments Research Center (NCERC). This set of polyethylene plates is designed to provide the optimal H/{sup 235}U ratio on the critical mass curve allowing the experiment to have the minimum amount of {sup 235}U. This makes a great teaching tool to show that either additional {sup 235}U or additional moderator would increase the critical mass. The optimal H/{sup 235}U ratio and increased hydrogen density compared to the previously used Lucite plates has reduced the critical mass by 34%, to 997.9 ± 0.65 g. The robustness of this experiment makes it ideal for hands on training. The fuel foils consist of thin highly enriched uranium (93 wt% {sup 235}U) metal foils laminated in plastic; each foil weighs approximately 68 grams. The fuel is interleaved between interstitial plates to attain a critical configuration. The critical configuration requires 14.5 fuel foils. Rossi-α experiments have been proposed as a method of benchmarking kinetics properties given by neutronics codes such as MCNP. (authors)

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2022

Preconditioned least‐squares Petrov–Galerkin reduced order models

Abstract In this article, we introduce a methodology for improving the accuracy and efficiency of reduced order models (ROMs) constructed using the least‐squares Petrov–Galerkin (LSPG) projection method through the introduction of preconditioning. Unlike prior related work, which focuses on preconditioning the linear systems arising within the ROM numerical solution procedure to improve linear solver performance, our approach leverages a preconditioning matrix directly within the minimization problem underlying the LSPG formulation. Applying preconditioning in this way has the potential to improve ROM accuracy for several reasons. First, preconditioning the LSPG formulation changes the norm defining the residual minimization, which can improve the residual‐based stability constant bounding the ROM solution's error. The incorporation of a preconditioner into the LSPG formulation can have the additional effect of scaling the components of the residual being minimized to make them roughly of the same magnitude, which can be beneficial when applying the LSPG method to problems with disparate scales (e.g., dimensional equations, multi‐physics problems). Importantly, we demonstrate that an “ideal preconditioned” LSPG ROM (a ROM in which the preconditioner is the inverse of the Jacobian of its corresponding full order model) emulates projection of the full order model solution increment onto the reduced basis. This quantity defines a lower bound on the error of a ROM solution for a given reduced basis. By designing preconditioners that approximate the Jacobian inverse—as is common in designing preconditioners for solving linear systems—it is possible to obtain a ROM whose error approaches this lower bound. The proposed approach is evaluated on several mechanical and thermo‐mechanical problems implemented within the Albany HPC code and run in the predictive regime, with prediction across material parameter space. We demonstrate numerically that the introduction of simple Jacobi, Gauss‐Seidel, and ILU preconditioners into the proper orthogonal decomposition/LSPG formulation reduces significantly the ROM solution error, the reduced Jacobian condition number, the number of nonlinear iterations required to reach convergence, and the wall time (thereby improving efficiency). Moreover, our numerical results reveal that the introduction of preconditioning can deliver a robust and accurate solution for test cases in which the unpreconditioned LSPG method fails to converge.

Lindsay, Payton↗
DOE OSTI2017

Genome Characterization of Oleaginous Aspergillus oryzae BCC7051: A Potential Fungal-Based Platform for Lipid Production

The selected robust fungus, Aspergillus oryzae strain BCC7051 is of interest for biotechnological production of lipid-derived products due to its capability to accumulate high amount of intracellular lipids using various sugars and agro-industrial substrates. Here in this paper, we report the genome sequence of the oleaginous A. oryzae BCC7051. The obtained reads were de novo assembled into 25 scaffolds spanning of 38,550,958 bps with predicted 11,456 protein-coding genes. By synteny mapping, a large rearrangement was found in two scaffolds of A. oryzae BCC7051 as compared to the reference RIB40 strain. The genetic relationship between BCC7051 and other strains of A. oryzae in terms of aflatoxin production was investigated, indicating that the A. oryzae BCC7051 was categorized into group 2 nonaflatoxin-producing strain. Moreover, a comparative analysis of the structural genes focusing on the involvement in lipid metabolism among oleaginous yeast and fungi revealed the presence of multiple isoforms of metabolic enzymes responsible for fatty acid synthesis in BCC7051. The alternative routes of acetyl-CoA generation as oleaginous features and malate/citrate/pyruvate shuttle were also identified in this A. oryzae strain. The genome sequence generated in this work is a dedicated resource for expanding genome-wide study of microbial lipids at systems level, and developing the fungal-based platform for production of diversified lipids with commercial relevance.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Multiphase Species Transport Modeling for Molten Salt Reactors in the System Analysis Module: Generation, Decay, Deposition, and Extraction of Insoluble Fission Products

With the increase of interests in the design and deployment of advanced reactor systems, a desire for simulation tools supporting system analysis of reactor operation and safety is rising. Molten salt reactors (MSRs), one of the advanced reactor systems, utilize liquid fused salt fuel as both coolant and fuel. During operation, MSR generates insoluble fission products, including noble metals and gases. The buildup of these species in fuel salt presents safety concerns as they may deposit on surfaces of critical components and produce excessive decay heat, causing the failure of system components. Timely removal of these noble metals and gases would ensure the safe operation of the reactor system. The dynamic nature of salt fuel system, involving the generation, decay, deposition, and extraction of noble metals and gases, calls for robust species transport models to facilitate system analysis and monitoring, and design of efficient species removal components. This paper concentrates on the development of a computational framework for species transport, consisting of multiphase transport model formulation, mass transfer between phases, numerical implementation in MOOSE environment, verification through Method of Manufacture Solutions (MMS) and validation against experimental data from the Molten Salt Reactor Experiment (MSRE). Integrating this framework into the System Analysis Module (SAM) code further enhances SAM’s capabilities for advanced reactor analysis in the future.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

CSULA Hydrogen Refueling Facility Performance Evaluation and Optimization

Throughout its history, Cal State LA has been in the forefront of advanced energy and transportation technologies. The station is located at the intersection of two major highways in Los Angeles region and has a convenient access. It is capable of producing up to 60 kg/day and can fuel 15-20 vehicles per day. Cal State LA had partnered with DOE to establish a robust station operation and performance data collection program. This consisted of equipping the station with additional instrumentation and collecting fueling performance data for several years. The data was further furnished to NREL for processing and agglomeration with data from other stations. In addition to fueling, maintenance and failure events were shared as well as hydrogen purity reports. The station has also undergone several upgrades in fueling protocols and hardware for improved performance and code compliance.

08 HYDROGEN↗
DOE OSTI2015

SU-E-J-16: Automatic Image Contrast Enhancement Based On Automatic Parameter Optimization for Radiation Therapy Setup Verification

Purpose: In RT patient setup 2D images, tissues often cannot be seen well due to the lack of image contrast. Contrast enhancement features provided by image reviewing software, e.g. Mosaiq and ARIA, require manual selection of the image processing filters and parameters thus inefficient and cannot be automated. In this work, we developed a novel method to automatically enhance the 2D RT image contrast to allow automatic verification of patient daily setups as a prerequisite step of automatic patient safety assurance. Methods: The new method is based on contrast limited adaptive histogram equalization (CLAHE) and high-pass filtering algorithms. The most important innovation is to automatically select the optimal parameters by optimizing the image contrast. The image processing procedure includes the following steps: 1) background and noise removal, 2) hi-pass filtering by subtracting the Gaussian smoothed Result, and 3) histogram equalization using CLAHE algorithm. Three parameters were determined through an iterative optimization which was based on the interior-point constrained optimization algorithm: the Gaussian smoothing weighting factor, the CLAHE algorithm block size and clip limiting parameters. The goal of the optimization is to maximize the entropy of the processed Result. Results: A total 42 RT images were processed. The results were visually evaluated by RT physicians and physicists. About 48% of the images processed by the new method were ranked as excellent. In comparison, only 29% and 18% of the images processed by the basic CLAHE algorithm and by the basic window level adjustment process, were ranked as excellent. Conclusion: This new image contrast enhancement method is robust and automatic, and is able to significantly outperform the basic CLAHE algorithm and the manual window-level adjustment process that are currently used in clinical 2D image review software tools.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Acoustic Codes in 2D Spherical Coordinate

Finite-difference methods are widely used to simulate infrasound propagation in the atmosphere. Flexibility of finite-difference scheme allows implementation of highly heterogeneous media for sound propagation as well as complex source models for sound generation. While full 3-D finite-difference methods have been utilized for local infrasound propagation with pronounced topography, 2-D modeling approach has been preferred for regional and global propagation as full 3-D methods generally require enormous computational resources. Infrasound propagation is often simulated with a second-order finite difference scheme. This lowest-order finite-difference scheme is robust and straightforward to implement complex boundary conditions, but the solution includes large error with numerical dispersion and dissipation. This large numerical error may make the second-order finite-difference not optimal for long range infrasound propagation modeling as the numerical dispersion degrades the accuracy of the solution unacceptably. Here, we developed a high-order finite-difference solver for long-range infrasound simulation. The high-order scheme is particularly popular for linear wave modeling in aeroacoustics owing to its low-dispersive and low-dissipative behavior. We develop and evaluate a high-order finite difference scheme in 2-D axisymmetric coordinates. The axisymmetry allows to approximate 3-D spherical sound propagation and amplitude attenuation by a 2-D method. AC2Dr is developed to simulate infrasound propagation in realistic atmosphere, but can be used for linear acoustic waves in general materials with background flow. AC2Dr in an axisymmetric coordinates allows for spherical radiation of acoustic waves from compact sources.

Sjogreen, Bjorn↗
DOE OSTI2017

Customizable de novo design strategies for DOCK: Application to HIVgp41 and other therapeutic targets

De novo design can be used to explore vast areas of chemical space in computational lead discovery. As a complement to virtual screening, from‐scratch construction of molecules is not limited to compounds in pre‐existing vendor catalogs. Here, we present an iterative fragment growth method, integrated into the program DOCK, in which new molecules are built using rules for allowable connections based on known molecules. The method leverages DOCK's advanced scoring and pruning approaches and users can define very specific criteria in terms of properties or features to customize growth toward a particular region of chemical space. The code was validated using three increasingly difficult classes of calculations: (1) Rebuilding known X‐ray ligands taken from 663 complexes using only their component parts (focused libraries), (2) construction of new ligands in 57 drug target sites using a library derived from ∼13M drug‐like compounds (generic libraries), and (3) application to a challenging protein‐protein interface on the viral drug target HIVgp41. The computational testing confirms that the de novo DOCK routines are robust and working as envisioned, and the compelling results highlight the potential utility for designing new molecules against a wide variety of important protein targets. © 2017 Wiley Periodicals, Inc.

Allen, William J.↗
DOE OSTI2017

Laser beam coupling with capillary discharge plasma for laser wakefield acceleration applications

One of the most robust approaches, demonstrated to date, of accelerating electron beams by laser-plasma sources is the utilization of plasma channels generated by the capillary discharges. Although the spatial structure of the installation is simple in principle, there may be some important effects caused by the open ends of the capillary, by the supplying channels etc., which require a detailed 3D modeling of the processes. In the present work, such simulations are performed using the code MARPLE. First, the process of capillary filling with cold hydrogen before the discharge is fired, through the side supply channels is simulated. Second, the simulation of the capillary discharge is performed with the goal to obtain a time-dependent spatial distribution of the electron density near the open ends of the capillary as well as inside the capillary. Lastly, to evaluate the effectiveness of the beam coupling with the channeling plasma wave guide and of the electron acceleration, modeling of the laser-plasma interaction was performed with the code INF&RNO.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Atomic forces from Dirac-Kohn-Sham equations: Implementation in flexible (APW+lo/LAPW)+LO basis set

The atomic forces formulation based on the Dirac-Kohn-Sham equation and the flexible (APW+lo/LAPW)+LO basis set is presented here. The formulation was implemented in the code FlapwMBPT and allows a user to easily switch between different basis functions of the augmentation type (APW or LAPW) and between different kind of local orbitals. Similar to the work (Phys.Rev.B 91 (2015) 035105), the implementation takes into account small discontinuities of the wave functions, density, and potential at the muffin-tin sphere boundaries. Applications to the materials with strong relativistic effects, such as $\alpha$-Uranium, PuCoGa$_{5}$, and FePt, demonstrate robustness of the method. The comparison of the calculated forces with the ones obtained by numerical differentiation of free energy shows close agreement with deviations about 0.1% or less.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Best practices in software development for robust and reproducible geoscientific models based on insights from the Global Carbon Budget's dynamic vegetation models

Computational models play an increasingly vital role in scientific research by enabling the numerical simulation of complex processes. Such models are also fundamental in geosciences. For instance, they offer critical insights into the impacts of global change on the Earth system today and in the future. Beyond their value as research tools, models are also software products and should therefore adhere to certain established software engineering standards. However, scientists are rarely trained as software developers, which can lead to potential deficiencies in software quality like unreadable, inefficient, or erroneous code. The complexity of models, coupled with their integration into broader workflows, also often makes it challenging to reproduce results, evaluate processes, and build upon them. In this paper, we review the state and current practices of the development processes of the state-of-the-art land surface models used by the Global Carbon Budget. We combine the experience of modelers from the respective research groups with the expertise of software engineers from tech companies to outline key principles and tools for improving software quality in research. We explore four main areas: (1) model testing and validation, (2) scientific, technical, and user documentation, (3) version control, continuous integration, and code review, and (4) the portability and reproducibility of workflows. Our review reveals that while modeling communities are incorporating many best practices, significant room for improvement remains in areas such as automated testing, automated documentation, and reproducibility. Therefore, we here identify and promote essential software engineering practices, including numerous examples of practices from within the community that can serve as guidelines for other models and could help streamline processes across the entire community. We conclude with an open-source example implementation of these principles, demonstrating portable and reproducible data flows, a continuous integration setup, and web-based visualizations. This example may serve as a practical resource for model developers, users, and all scientists engaged in scientific programming.

Gregor, Konstantin [Technical Univ. of Munich (Ger↗
DOE OSTI2015

Theoretical study of chemical reactions in solution

Quantum chemical calculations in solution are becoming more and more important in chemistry. Reference interaction site model self-consistent field (RISM-SCF) is one of the powerful approaches to perform quantum chemical calculations in solution. In this work, we developed a new generation of RISM-SCF, where a robust fitting method was newly introduced. We applied the new method to tautomerization reaction of cytosine in aqueous phase. Our calculation reproduced experimentally obtained relative stabilities and relative free energies correctly.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

INTEGRATE - Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements

The INTEGRATE (Inverse Network Transformations for Efficient Generation of Robust Airfoil and Turbine Enhancements) project is developing a new inverse-design capability for the aerodynamic design of wind turbine rotors using invertible neural networks. This AI-based design technology can capture complex non-linear aerodynamic effects while being 100 times faster than design approaches based on computational fluid dynamics. This project enables innovation in wind turbine design by accelerating time to market through higher-accuracy early design iterations to reduce the levelized cost of energy. INVERTIBLE NEURAL NETWORKS Researchers are leveraging a specialized invertible neural network (INN) architecture along with the novel dimension-reduction methods and airfoil/blade shape representations developed by collaborators at the National Institute of Standards and Technology (NIST) learns complex relationships between airfoil or blade shapes and their associated aerodynamic and structural properties. This INN architecture will accelerate designs by providing a cost-effective alternative to current industrial aerodynamic design processes, including: - Blade element momentum (BEM) theory models: limited effectiveness for design of offshore rotors with large, flexible blades where nonlinear aerodynamic effects dominate - Direct design using computational fluid dynamics (CFD): cost-prohibitive - Inverse-design models based on deep neural networks (DNNs): attractive alternative to CFD for 2D design problems, but quickly overwhelmed by the increased number of design variables in 3D problems AUTOMATED COMPUTATIONAL FLUID DYNAMICS FOR TRAINING DATA GENERATION - MERCURY FRAMEWORK The INN is trained on data obtained using the University of Marylands (UMD) Mercury Framework, which has with robust automated mesh generation capabilities and advanced turbulence and transition models validated for wind energy applications. Mercury is a multi-mesh paradigm, heterogeneous CPU-GPU framework. The framework incorporates three flow solvers at UMD, 1) OverTURNS, a structured solver on CPUs, 2) HAMSTR, a line based unstructured solver on CPUs, and 3) GARFIELD, a structured solver on GPUs. The framework is based on Python, that is often used to wrap C or Fortran codes for interoperability with other solvers. Communication between multiple solvers is accomplished with a Topology Independent Overset Grid Assembler (TIOGA). NOVEL AIRFOIL SHAPE REPRESENTATIONS USING GRASSMAN SPACES We developed a novel representation of shapes which decouples affine-style deformations from a rich set of data-driven deformations over a submanifold of the Grassmannian. The Grassmannian representation as an analytic generative model, informed by a database of physically relevant airfoils, offers (i) a rich set of novel 2D airfoil deformations not previously captured in the data , (ii) improved low-dimensional parameter domain for inferential statistics informing design/manufacturing, and (iii) consistent 3D blade representation and perturbation over a sequence of nominal shapes. TECHNOLOGY TRANSFER DEMONSTRATION - COUPLING WITH NREL WISDEM Researchers have integrated the inverse-design tool for 2D airfoils (INN-Airfoil) into WISDEM (Wind Plant Integrated Systems Design and Engineering Model), a multidisciplinary design and optimization framework for assessing the cost of energy, as part of tech-transfer demonstration. The integration of INN-Airfoil into WISDEM allows for the design of airfoils along with the blades that meet the dynamic design constraints on cost of energy, annual energy production, and the capital costs. Through preliminary studies, researchers have shown that the coupled INN-Airfoil + WISDEM approach reduces the cost of energy by around 1% compared to the conventional design approach. This page will serve as a place to easily access all the publications from this work and the repositories for the software developed and released through this pr...

aerodynamics↗
DOE OSTI2021

GR-Athena++: Puncture Evolutions on Vertex-centered Oct-tree Adaptive Mesh Refinement

Numerical relativity is central to the investigation of astrophysical sources in the dynamical and strong-field gravity regime, such as binary black hole and neutron star coalescences. Current challenges set by gravitational-wave and multimessenger astronomy call for highly performant and scalable codes on modern massively parallel architectures. We present GR-Athena++, a general-relativistic, high-order, vertex-centered solver that extends the oct-tree, adaptive mesh refinement capabilities of the astrophysical (radiation) magnetohydrodynamics code Athena++. To simulate dynamical spacetimes, GR-Athena++ uses the Z4c evolution scheme of numerical relativity coupled to the moving puncture gauge. We demonstrate stable and accurate binary black hole merger evolutions via extensive convergence testing, cross-code validation, and verification against state-of-the-art effective-one-body waveforms. GR-Athena++ leverages the task-based parallelism paradigm of Athena++ to achieve excellent scalability. We measure strong-scaling efficiencies above 95% for up to ~1.2 × 10 4 CPUs and excellent weak scaling is shown up to ~10 5 CPUs in a production binary black hole setup with adaptive mesh refinement. GR-Athena++ thus allows for the robust simulation of compact binary coalescences and offers a viable path toward numerical relativity at exascale.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Multiphysics Time-Integration for Turbulent Combustion at the Exascale

Turbulent reacting flow systems are often modeled with coupled time-dependent partial differential equations (PDEs). Solving such equations can easily tax the world's largest supercomputers. One pragmatic strategy for attacking such problems is to split the PDEs into components that can more easily be solved in isolation. This generic operator-splitting strategy leads to a set of ordinary differential equations (ODEs) that need to be solved as part of an "outer-loop" time-stepping approach. In many combustion applications, the ODEs to be solved can be very stiff, exhibiting timescales that span many orders of magnitude. The SUNDIALS library provides a plethora of robust time integration algorithms for solving these ODEs on exascale-capable computing hardware, yet for many complex applications (such multicomponent fuels or emissions predictions), the chemical models remain too complex to solve using reasonable resources. The Quasi-Steady State Approximation (QSSA) can be an effective tool for reducing the size and stiffness of the simulations. In this talk, I will discuss the use of the SUDIALS library of ODE solvers together with automatic code generation tools to solve complex turbulent reacting flow problems using QSSA models.

chemistry↗
DOE OSTI2021

Photosynthetic reaction center variants made via genetic code expansion show Tyr at M210 tunes the initial electron transfer mechanism

Significance Reaction centers (RCs) are critical to photosynthetic energy conversion. RCs in all characterized photosynthetic organisms contain two symmetrically arranged branches of chromophores and enable light-induced electron transfer with high yield. We fine-tune the properties of a key bacterial RC symmetry-breaking tyrosine via its replacement with noncanonical tyrosine analogs and determine kinetic outcomes. Results are interpreted through energetic characterization made possible by resonance Stark spectroscopy. Analysis indicates this tyrosine modulates the mechanism of the initial light-induced electron transfer, affording an alternative functional pathway that maintains the RC’s robust electron transfer. Modern molecular biology, ultrafast spectroscopy, crystallography, and energetic characterization enable the mechanistic model we describe. Our results deepen understanding of RC function and may have implications for other photocatalysts and enzymes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

MCNP Simulation of Discrete Gamma-ray Spectra for PGNAA Applications

Prompt Gamma Neutron Activation (PGNAA) systems use the neutron-induced gamma-ray spectra from test objects in order to identify their compositions. The U.S. Army in particular uses these systems to identify the contents of field-recovered munitions in order to determine the presence of chemical warfare materiel (CWM) or explosives. These field-recovered munitions can have a variety of different fills, including experimental fills, have a large range of sizes, and be assessed in different field conditions. All these variations can have a significant effect on the neutron-induced gamma-ray spectrum and therefore a large impact on automatic fill identification algorithms. In order to develop robust identification algorithms, parametric studies of the effects of munition size, fill composition, and assessment conditions are very useful but time-consuming and expensive in the laboratory. Monte Carlo modeling of the system response to these variations is a very attractive alternative, provided the modeling accurately reflects real gamma spectra and can be performed quickly and inexpensively when compared to experiment. At Idaho National Laboratory we have used the Monte Carlo N-Particle (MCNP6) code [2] to calculate the response of the Portable Isotopic Neutron Spectroscopy (PINS) system to a number of simulated chemical warfare munitions as well as performed laboratory measurements with the system. Two versions of PINS system were used; one excited the test object with neutrons from a 252C f source and one with neutrons from a portable deuterium-deuterium (DD) neutron generator. The sets of measurements and simulations with the two different neutron sources provided experimental data for development of automatic fill identification algorithms as well as providing a good test of the agreement between the MCNP calculations and experiment.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗